Using environment objects as tools in unknown environments

Robots should be able to reason about using objects in the environment to assist task completion. If faced with an unexpected situation, such as a critically damaged floor, robots should be able to evaluate different ways to resolve the situation rather than directly declaring failure. In this paper, we present the first online framework that enables robots to reason about using environment objects as tools to overcome obstructions, allowing robots to solve previously unsolvable tasks. The framework utilizes constraint relaxed planning to detect unavoidable obstructions. In case the robot becomes disconnected from the goal by an obstruction, the system guides the robot to search for and utilize an object in the environment to overcome the obstruction using the concept of inverse affordances. We verified the framework in a realistic simulation environment for the PR2 robot.